Type 2 diabetes mellitus (T2DM or “diabetes”) is one of the most costly and burdensome chronic diseases in the U.S. and other countries. The defining feature of T2DM is hyperglycemia, a reflection of impaired carbohydrate (glucose) utilization resulting from a defective or deficient insulin secretory response. T2DM is a late manifestation of metabolic derangements that begin many years earlier. Its cause is believed to be a progressive increase in insulin resistance coupled with deteriorating β-cell function. So long as the pancreatic β-cells are able to secrete enough insulin to compensate for the progressive resistance of target tissues to insulin's hypoglycemic effects, the patient is able to maintain normal fasting glucose levels. Hyperglycemia and the transition to T2DM occur as a consequence of progressive β-cell dysfunction which leads to failure to maintain hypersecretion of insulin in the face of increasing insulin resistance.
Type 2 diabetes has been traditionally diagnosed by the detection of elevated levels of glucose (sugar) in the blood (hyperglycemia). While hyperglycemia defines diabetes, it is a very late stage development in the chain of events that lead from insulin resistance to full-blown diabetes. Accordingly, it would be desirable to have a way of identifying whether or not a subject is at risk for developing Type 2 diabetes (i.e., is predisposed to the condition) prior to the development of the classic symptoms, such as hyperglycemia. Earlier detection of indicators of the disease (e.g., detection before glucose levels are elevated enough to be considered hyperglycemia) may lead to more effective treatment of the disease, if not actual prevention of the onset of the disease.
The most direct and accurate methods for assessing insulin resistance are laborious and time-consuming, and thus impractical for clinical application. The “gold standard” among these research methods is the hyperinsulinemic euglycemic clamp, which quantifies the maximal glucose disposal rate (GDR, inversely proportional to insulin resistance) during the clamp. Another arduous research method which is somewhat less reproducible (CV 14-30%) is the frequently sampled intravenous glucose tolerance test (IVGTT) with minimal model analysis, which measures insulin sensitivity (Si), the inverse of insulin resistance.
Risk of progression to Type 2 diabetes is currently assessed primarily by fasting glucose, with concentrations 100-125 mg/dL defining a high-risk “pre-diabetes” condition and for which T2DM is currently defined in patients having fasting plasma glucose levels at 126 mg/dL and above. However, the actual risk of individual patients with pre-diabetes (those at greatest risk of developing T2DM in the near future) varies widely.
NMR spectroscopy has been used to concurrently measure low density lipoproteins (LDL), high density lipoproteins (HDL), and very low density lipoproteins (VLDL), as LDL, HDL and VLDL particle subclasses from in vitro blood plasma or serum samples. See, U.S. Pat. Nos. 4,933,844 and 6,617,167, the contents of which are hereby incorporated by reference as if recited in full herein. U.S. Pat. No. 6,518,069 to Otvos et al. describes NMR derived measurements of glucose and/or certain lipoprotein values to assess a patient's risk of developing T2DM.
Generally stated, to evaluate the lipoproteins in a blood plasma and/or serum sample, the amplitudes of a plurality of NMR spectroscopy derived signals within a chemical shift region of NMR spectra are derived by deconvolution of the composite methyl signal envelope to yield subclass concentrations. The subclasses are represented by many (typically over 60) discrete contributing subclass signals associated with NMR frequency and lipoprotein diameter. The NMR evaluations can interrogate the NMR signals to produce concentrations of different subpopulations, typically seventy-three discrete subpopulations, 27 for VLDL, 20 for LDL and 26 for HDL. These sub-populations can be further characterized as associated with a particular size range within the VLDL, LDL or HDL subclasses.
An advanced lipoprotein test panel, such as the LIPOPROFILE® lipoprotein test, available from LipoScience, Raleigh, N.C., has typically included a total high density lipoprotein particle (HDL-P) measurement (e.g., HDL-P number) that sums the concentration of all the HDL subclasses and a total low density lipoprotein particle (LDL-P) measurement that sums the concentration of all the LDL subclasses (e.g., LDL-P number). The LDL-P and HDL-P numbers represent the concentration of those respective particles in concentration units such as nmol/L. LipoScience has also developed a lipoprotein-based insulin resistance and sensitivity index (the “LP-IR™” index) as described in U.S. Pat. No. 8,386,187, the contents of which are hereby incorporated by reference as if recited in full herein.
Despite the foregoing, there remains a need for evaluations that can predict or assess a person's risk of developing type 2 diabetes before the onset of the disease.